185 citations · 778 across the 44 of their papers we have counts for
4 papers · 1 filter
Elastic On-Device LLM Service
Wangsong Yin, Rongjie Yi, Daliang Xu +3
On-device Large Language Models (LLMs) are transforming mobile AI, catalyzing applications like UI automation without privacy concerns. Nowadays the common practice is to deploy a…
Energy-Efficient GPU Clusters Scheduling for Deep Learning
Diandian Gu, Xintong Xie, Gang Huang +2
Training deep neural networks (DNNs) is a major workload in datacenters today, resulting in a tremendously fast growth of energy consumption. It is important to reduce the energy c…
MuxFlow: Efficient and Safe GPU Sharing in Large-Scale Production Deep Learning Clusters
Yihao Zhao, Xin Liu, Shufan Liu +5
Large-scale GPU clusters are widely-used to speed up both latency-critical (online) and best-effort (offline) deep learning (DL) workloads. However, most DL clusters either dedicat…
FaaSLight: General Application-Level Cold-Start Latency Optimization for Function-as-a-Service in Serverless Computing
Xuanzhe Liu, Jinfeng Wen, Zhenpeng Chen +5
Serverless computing is a popular cloud computing paradigm that frees developers from server management. Function-as-a-Service (FaaS) is the most popular implementation of serverle…